{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "google",
   "metadata": {},
   "source": [
    "##### Copyright 2023 Google LLC."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apache",
   "metadata": {},
   "source": [
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "basename",
   "metadata": {},
   "source": [
    "# clone_model_sample_sat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "link",
   "metadata": {},
   "source": [
    "<table align=\"left\">\n",
    "<td>\n",
    "<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/sat/clone_model_sample_sat.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
    "</td>\n",
    "<td>\n",
    "<a href=\"https://github.com/google/or-tools/blob/main/ortools/sat/samples/clone_model_sample_sat.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
    "</td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "doc",
   "metadata": {},
   "source": [
    "First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "install",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install ortools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "description",
   "metadata": {},
   "source": [
    "\n",
    "Showcases deep copying of a model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "code",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ortools.sat.python import cp_model\n",
    "\n",
    "\n",
    "def CloneModelSampleSat():\n",
    "    \"\"\"Showcases cloning a model.\"\"\"\n",
    "    # Creates the model.\n",
    "    model = cp_model.CpModel()\n",
    "\n",
    "    # Creates the variables.\n",
    "    num_vals = 3\n",
    "    x = model.NewIntVar(0, num_vals - 1, \"x\")\n",
    "    y = model.NewIntVar(0, num_vals - 1, \"y\")\n",
    "    z = model.NewIntVar(0, num_vals - 1, \"z\")\n",
    "\n",
    "    # Creates the constraints.\n",
    "    model.Add(x != y)\n",
    "\n",
    "    model.Maximize(x + 2 * y + 3 * z)\n",
    "\n",
    "    # Creates a solver and solves.\n",
    "    solver = cp_model.CpSolver()\n",
    "    status = solver.Solve(model)\n",
    "\n",
    "    if status == cp_model.OPTIMAL:\n",
    "        print(\"Optimal value of the original model: {}\".format(solver.ObjectiveValue()))\n",
    "\n",
    "    # Clone the model.\n",
    "    copy = model.Clone()\n",
    "\n",
    "    copy_x = copy.GetIntVarFromProtoIndex(x.Index())\n",
    "    copy_y = copy.GetIntVarFromProtoIndex(y.Index())\n",
    "\n",
    "    copy.Add(copy_x + copy_y <= 1)\n",
    "\n",
    "    status = solver.Solve(copy)\n",
    "\n",
    "    if status == cp_model.OPTIMAL:\n",
    "        print(\"Optimal value of the modified model: {}\".format(solver.ObjectiveValue()))\n",
    "\n",
    "\n",
    "CloneModelSampleSat()\n",
    "\n"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}
